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September 12, 2025

Adversarial Machine Learning in Cybersecurity: Vulnerabilities and Defense Strategies

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Authors

LBLawal Abdulmutalib BabatundeEEEdima David EtimIEIboro Akpan Essien

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Overview

This analysis reveals threats from adversarial machine learning in cybersecurity, highlighting vulnerabilities and defense strategies.

Key Points

  • Adversarial machine learning creates vulnerabilities that may undermine cybersecurity systems and their effectiveness.
  • Evasion attacks undermine detection systems, showing that even slight input perturbations can have significant consequences.
  • This comprehensive analysis of adversarial threats utilizes case studies, showcasing vulnerabilities in deep learning, support vector machines, and ensemble methods.
  • Robust defense strategies against adversarial machine learning are essential for maintaining the integrity and reliability of cybersecurity applications.

Cite This Study

Babatunde et al. (2020) studied this question.

synapsesocial.com/papers/68d4768331b076d99fa6f025https://doi.org/10.54660/.jfmr.2020.1.2.31-45
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